Hannes Schwandt

Within-mother analysis of seasonal patterns in health at birth

A large literature describes relationships between month of birth, birth weight, and gestation. These relationships are hypothesized to reflect the causal impact of seasonal environmental factors. However, recent work casts doubt on this interpretation by showing that mothers with lower socioeconomic status are more likely to give birth in months that are associated with poorer birth outcomes. Seasonality in the numbers of conceptions in different months can also induce a mechanical correlation between preterm birth and month of birth. This paper analyzes the seasonality of health at birth using a large sample of 647,050 groups of US siblings representing 1,435,213 children. By following the same mother over time, we eliminate differences in fixed maternal characteristics as an explanation for seasonal differences in health at birth. We find a sharp trough in gestation length among babies conceived in May, which corresponds to an increase in prematurity of more than 10%. Birth weight conditional on gestation length, however, is found to be strongly hump-shaped over the year, with 8–9 additional g for summer conceptions. We examine several potential mechanisms for explaining seasonality in birth outcomes that have generally been dismissed in the literature on seasonality in rich countries, notably disease prevalence and nutrition. The May trough in gestation length coincides with a higher influenza prevalence in January and February, when these babies are nearing full term, whereas the hump shape in birth weight is associated with a similar pattern in pregnancy weight gain.

Short and long-term effects of unemployment on fertility

Significance Fertility falls when unemployment rises, but there may be no long-run effect if women simply postpone childbearing. We analyze the effects of unemployment by following fixed cohorts of US-born women defined by their own state and year of birth. We find that a one percentage point increase in the unemployment rate experienced between the ages of 20 and 24 reduces the short-run fertility of women in this age range by six conceptions per 1,000 women. When these women are followed to age 40, a one percentage point increase in the unemployment rate experienced at 20 to 24 is associated with an overall loss of 14.2 conceptions. This larger long-term effect is driven largely by women who remain childless. Scholars have been examining the relationship between fertility and unemployment for more than a century. Most studies find that fertility falls with unemployment in the short run, but it is not known whether these negative effects persist, because women simply may postpone childbearing to better economic times. Using more than 140 million US birth records for the period 1975–2010, we analyze both the short- and long-run effects of unemployment on fertility. We follow fixed cohorts of US-born women defined by their own state and year of birth, and relate their fertility to the unemployment rate experienced by each cohort at different ages. We focus on conceptions that result in a live birth. We find that women in their early 20s are most affected by high unemployment rates in the short run and that the negative effects on fertility grow over time. A one percentage point increase in the average unemployment rate experienced between the ages of 20 and 24 reduces the short-run fertility of women in this age range by six conceptions per 1,000 women. When we follow these women to age 40, we find that a one percentage point increase in the unemployment rate experienced at ages 20–24 leads to an overall loss of 14.2 conceptions. This long-run effect is driven largely by women who remain childless and thus do not have either first births or higher-order births.

Inequality in mortality decreased among the young while increasing for older adults, 1990–2010

Narrowing of the life expectancy gap In the United States, the rich can expect to enjoy better health and a longer life than the poor. Despite policies directed at improving the health of both the young and the poor, there is little evidence that this relationship has changed. Currie and Schwandt looked specifically at the life expectancy of present-day children and young adults, finding that mortality inequality has in fact declined over the past 25 years (see the Perspective by Bailey and Timpe). Science, this issue p. 708; see also p. 661 U.S. social policies aimed at helping poor families have increased life expectancy and decreased mortality. Many recent studies point to increasing inequality in mortality in the United States over the past 20 years. These studies often use mortality rates in middle and old age. We used poverty level rankings of groups of U.S. counties as a basis for analyzing inequality in mortality for all age groups in 1990, 2000, and 2010. Consistent with previous studies, we found increasing inequality in mortality at older ages. For children and young adults below age 20, however, we found strong mortality improvements that were most pronounced in poorer counties, implying a strong decrease in mortality inequality. These younger cohorts will form the future adult U.S. population, so this research suggests that inequality in old-age mortality is likely to decline.

Unmet Aspirations as an Explanation for the Age U-Shape in Human Wellbeing

A large literature in behavioral and social sciences has found that human wellbeing follows a U-shape over age. Some theories have assumed that the U-shape is caused by unmet expectations that are felt painfully in midlife but beneficially abandoned and experienced with less regret during old age. In a unique panel of 132,609 life satisfaction expectations matched to subsequent realizations, I find people to err systematically in predicting their life satisfaction over the life cycle. They expect -- incorrectly -- increases in young adulthood and decreases during old age. These errors are large, ranging from 9.8% at age 21 to -4.5% at age 68, they are stable over time and observed across socio-economic groups. These findings support theories that unmet expectations drive the age U-shape in wellbeing.

Poorly Measured Confounders Are More Useful On the Left than On the Right

ABSTRACT Researchers frequently test identifying assumptions in regression-based research designs (which include instrumental variables or difference-in-differences models) by adding additional control variables on the right-hand side of the regression. If such additions do not affect the coefficient of interest (much), a study is presumed to be reliable. We caution that such invariance may result from the fact that the observed variables used in such robustness checks are often poor measures of the potential underlying confounders. In this case, a more powerful test of the identifying assumption is to put the variable on the left-hand side of the candidate regression. We provide derivations for the estimators and test statistics involved, as well as power calculations, which can help applied researchers interpret their findings. We illustrate these results in the context of estimating the returns to schooling.

The 9/11 Dust Cloud and Pregnancy Outcomes: A Reconsideration

The events of 9/11 released a million tons of toxic dust into lower Manhattan, an unparalleled environmental disaster. It is puzzling, then, that the literature has shown little effect of fetal exposure to the dust. However, inference is complicated by preexisting differences between the affected mothers and other NYC mothers as well as heterogeneity in effects on boys and girls. Using all births in-utero on 9/11 in NYC and comparing them to their siblings, we show that residence in the affected area increased prematurity and low birth weight, especially for boys.